New Predictor and 2DOF Control Scheme for Industrial Processes with Long Time Delay

© 2018 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] To address the difficulty of controlling industrial processes with long time delay, a novel design of dead-time compensator (DTC) is introduced, which can be used to predict the undelayed output response of any process (no matter stable or unstable) such that the control design may be focused on the delay-free part of the process for performance optimization. Based on the undelayed output estimation, a two-degree-of-freedom (2DOF) control scheme is analytically developed for optimizing the set-point tracking and disturbance rejection, respectively. By proposing the desired transfer functions, the corresponding controllers are analytically derived based on commonly used low-order process models. A notable advantage is that there is a single adjustable parameter in the proposed DTC, as well as in each controller, which can be monotonically tuned to meet a good tradeoff between the prediction (or control) performance and its robustness. Illustrative examples from the literature and a practical application to a temperature control system of a jacketed reactor are used to demonstrate the effectiveness of the proposed predictor-based control scheme.This work was supported in part by the NSF China under Grant 61633006 and Grant 61473054; in part by the National Thousand Talents Program of China, the PROMETEOII/2013/004, Conselleria d'Educacio, Generalitat Valenciana, and TIN2014-56158-C4-4-P-AR; in part by the Ministerio de Economia y Competitividad; and in part by the FPI-UPV 2014 Grant Program from the Universidad Politecnica de Valencia, Valencia, SpainLiu, T.; García Gil, PJ.; Chen, Y.; Ren, X.; Albertos Pérez, P.; Sanz Diaz, R. (2018). New Predictor and 2DOF Control Scheme for Industrial Processes with Long Time Delay. IEEE Transactions on Industrial Electronics. 65(5):4247-4256. https://doi.org/10.1109/TIE.2017.2760839S4247425665

Analytical design of a generalised predictor-based control scheme for low-order integrating and unstable systems with long time delay

In this study, the problem of controlling integrating and unstable systems with long time delay is analysed in the discrete-time domain for digital implementation. Based on a generalised predictor-based control structure, where the plant time delay can be taken out of the control loop for the nominal plant, an analytical controller design is proposed in terms of the delay-free part of the nominal plant model. Correspondingly, further improved control performance is obtained compared with recently developed predictor-based control methods relying on numerical computation for controller parameterisation. The load disturbance rejection controller is derived by proposing the desired closed-loop transfer function, and another one for set-point tracking is designed in terms of the H-2 optimal control performance specification. Both controllers can be tuned relatively independently in a monotonic manner, with a single adjustable parameter in each controller. By establishing the sufficient and necessary condition for holding robust stability of the closed-loop control system, tuning constraints are derived together with numerical tuning guidelines for the disturbance rejection controller. Illustrative examples taken from the literature along with temperature control tests for a crystallisation reactor are used to demonstrate the effectiveness and merit of the proposed method.This work was supported in part by the National Thousand Talents Program of China, NSF China Grants 61473054, the Fundamental Research Funds for the Central Universities of China, and the Grants TIN2014-56158-C4-4-P and PROMETEOII/2013/004 from the Spanish and Valencian Governments.Chen, Y.; Liu, T.; García Gil, PJ.; Albertos Pérez, P. (2016). Analytical design of a generalised predictor-based control scheme for low-order integrating and unstable systems with long time delay. IET Control Theory and Applications. 10(8):884-893. https://doi.org/10.1049/iet-cta.2015.0670S88489310

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Identification and self-tuning control of time-delay systems

Time-delays (dead times) occur in many processes in industry. A Toolbox in the MATLAB/SIMULINK environment was designed for identification and self-tuning control of such processes. The control algorithms are based on modifications of the Smith Predictor (SP). The designed algorithms that are included in the toolbox are suitable not only for simulation purposes but also for implementation in real time conditions. Verification of the designed Toolbox is demonstrated on a self-tuning control of a laboratory heat exchanger in simulation conditions

Predictor-based robust control of dead-time processes

Tese (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.Esta tese trata do problema de controle robusto de sistemas não-lineares com atraso utilizando estruturas de compensação de atraso. Como já descrito na literatura, três são os problemas causados pela presença de atraso de transporte: (i) os efeitos das perturbações não são notados até se passar o tempo do atraso, (ii) o efeito da ação de controle demora para ser notado na variável controlada, e (iii) a ação de controle que é aplicada no instante atual tenta corrigir uma situação que se originou tempos atrás. Uma das mais utilizadas soluções para evitar (ou atenuar) esses efeitos é o uso do Preditor de Smith (SP - Smith Predictor). Preditores são estruturas que permitem o controle de processos com atraso a partir de um modelo sem atraso, o que simplifica o ajuste do controlador. Uma importante propriedade do Preditor de Smith vem do fato de que a robustez do sistema de malha fechada resultante não depende do valor nominal do atraso. Esta propriedade, no entanto, não é válida para qualquer preditor. Por exemplo, algoritmos de controle preditivo (MPC - Model Based Predictive Controllers) definem implicitamente estruturas preditoras, mas, como já foi mostrado na literatura, no caso específico do GPC (Generalized Predictive Control), o preditor ótimo definido implicitamente faz com que a robustez do sistema dependa do valor nominal do atraso. Também já havia sido mostrado que, substituindo este preditor implícito por um Preditor de Smith Filtrado (FSP - Filtered Smith Predictor), resulta em um controlador mais robusto que herda as características do SP. Assim, os objetivos desta tese são: (i) Estudo do algoritmo preditivo Dynamic Matrix Control (DMC), através de uma estrutura FSP, e propor modificações que permitam melhorar a rejeição de perturbações e/ou aumentar a robustez do sistema; (ii) análise e implementação de uma estrutura baseada no FSP para sistemas não-lineares. Os algoritmos de controle preditivo, ou MPC, emergiram durante as últimas três décadas como uma poderosa solução de controle, e obtiveram um impacto significativo na indústria, como já mostrado em diversos trabalhos. No entanto, apesar de grandes avanços teóricos e do fato de que os processos industriais são, em geral, não lineares, a maioria das técnicas de controle aplicadas na indústria são baseadas em modelos lineares. Algoritmos MPC simples baseados em modelos de resposta ao degrau (ou impulsiva) sem garantia de estabilidade são os mais comuns na indústria, principalmente em refinarias e plantas petroquímicas. Algumas razões para isso são: (i) os processos possuem comportamento estável em malha aberta e ajustando adequadamente os parâmetros do controlador é possível obter a estabilidade do sistema em malha fechada, e (ii) modelos lineares são suficientes quando o processo está operando próximo de um ponto de operação. Desta forma, a análise das propriedades de malha fechada desses controladores, como velocidade de rejeição de perturbação e robustez, é muito importante para a indústria de processos, já que é possível obter modificações simples e úteis que melhoram o desempenho de aplicações reais. Assim, neste trabalho, o algoritmo preditivo DMC será interpretado através da estrutura FSP de forma que os efeitos do atraso no sistema de malha fechada possam ser entendidos. Esta abordagem foi escolhida por permitir que várias técnicas de sintonia já desenvolvidas para o FSP possam ser aplicadas ao DMC. Será mostrado que o algoritmo DMC precisa apenas de pequenas modificações para adquirir as vantagens fornecidas pela estrutura FSP. O segundo tópico deste trabalho trata de estruturas preditoras para sistemas não-lineares. Seguindo as ideias propostas para o caso linear, neste trabalho será proposto o Preditor de Smith Filtrado para Sistemas Não-Lineares (NLFSP - Nonlinear Filtered Smith Predictor), que permitirá melhorar as características de robustez e rejeição de perturbação de sistemas não lineares. Já há trabalhos evidenciando algumas vantagens do FSP para sistemas não-lineares, no entanto não há provas nem uma análise formal de suas propriedades. O FSP linear possui as seguintes características: (i) a resposta nominal para mudanças de referência não é afetada pela inserção do filtro de predição; (ii) a robustez pode ser melhorada ajustando o filtro adequadamente; (iii) o filtro de predição pode ser ajustado para acelerar a rejeição de perturbações. Vários exemplos de simulação são apresentados no documento para ilustrar os resultados teóricos apresentados. Em particular, se aplicam os resultados a processos da indústria do petróleo e petroquímica onde os controladores preditivos têm um grande impacto.Abstract : This thesis deals with the analysis and design of predictor-based robust controllers for processes with dead time. The main objectives are: (i) to analyze the effect of the predictor structure in the closed-loop behavior and robustness of linear and nonlinear controllers; (ii) to propose better predictor structures to improve robustness and performance of control loops; (iii) to apply the results in simulated and real industrial processes, mainly for the petroleum industry. The results of this thesis are: an improvement on the well-known Dynamic Matrix Control (DMC) algorithm, from the Model Predictive Control (MPC) family, and a predictor for nonlinear systems with time delay based on the Smith Predictor. Concerning the MPC, in this work, an improved industrial MPC controller based on the widely used DMC approach is presented. A MIMO filter is included in the prediction model of the controller in order to achieve two important advantages when compared to traditional industrial DMC: (i) disturbance rejection response can be speeded up and (ii) robustness can be improved, mainly when errors in the estimation of the delays are considered. The filter properties are demonstrated by means of an equivalent analysis of the unconstrained DMC using a dead time compensation (DTC) approach, namely the Filtered Smith Predictor. Moreover, implementation and tuning of the filter is simple and intuitive. Simulation results using a water-methanol distillation column are presented to illustrate the advantages of the proposed approach. For the case of nonlinear processes with time delay, a Nonlinear Filtered Smith Predictor (NLFSP) structure is proposed for nonlinear systems. It will be shown that the NLFSP maintains the characteristics of the linear Smith Predictor and that, with appropriate tuning, it can increase the robustness of the closed-loop system. The NLFSP is applied to various examples and case studies to demonstrate these characteristics